Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark
Hao Sun, Guangxuan Xu, Jiawen Deng, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2022), pp. 3906-3923
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

COLD: A Benchmark for Chinese Offensive Language Detection
Jiawen Deng, Jingyan Zhou, Hao Sun, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 50
ProsocialDialog: A Prosocial Backbone for Conversational Agents
Hyunwoo Kim, Youngjae Yu, Liwei Jiang, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 36
AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation
Chujie Zheng, Sahand Sabour, Jiaxin Wen, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2023)
Open Access | Times Cited: 20
SafetyKit: First Aid for Measuring Safety in Open-domain Conversational Systems
Emily Dinan, Gavin Abercrombie, A. Bergman, et al.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
Open Access | Times Cited: 28
EVA2.0: Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training
Yuxian Gu, Jiaxin Wen, Hao Sun, et al.
Deleted Journal (2023) Vol. 20, Iss. 2, pp. 207-219
Open Access | Times Cited: 15
Bots, disinformation, and the first impeachment of U.S. President Donald Trump
Michael Rossetti, Tauhid Zaman
PLoS ONE (2023) Vol. 18, Iss. 5, pp. e0283971-e0283971
Open Access | Times Cited: 14
Mirages. On Anthropomorphism in Dialogue Systems
Gavin Abercrombie, Amanda Cercas Curry, Tanvi Dinkar, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 14
Comparative Analysis of Artificial Intelligence Virtual Assistant and Large Language Models in Post-Operative Care
Sahar Borna, Cesar A. Gomez-Cabello, Sophia M. Pressman, et al.
European Journal of Investigation in Health Psychology and Education (2024) Vol. 14, Iss. 5, pp. 1413-1424
Open Access | Times Cited: 6
Rethinking Conversational Agents in the Era of LLMs: Proactivity, Non-collaborativity, and Beyond
Yang Deng, Wenqiang Lei, Minlie Huang, et al.
(2023)
Closed Access | Times Cited: 10
Proactive Conversational AI: A Comprehensive Survey of Advancements and Opportunities
Yang Deng, Lizi Liao, Wenqiang Lei, et al.
ACM transactions on office information systems (2025)
Closed Access
PANDA – Paired Anti-hate Narratives Dataset from Asia: Using an LLM-as-a-Judge to Create the First Chinese Counterspeech Dataset
Michael Bennie, Demi Zhang, Bushi Xiao, et al.
(2025)
Open Access
Towards Identifying Social Bias in Dialog Systems: Framework, Dataset, and Benchmark
Jingyan Zhou, Jiawen Deng, Fei Mi, et al.
(2022), pp. 3576-3591
Open Access | Times Cited: 16
SafeText: A Benchmark for Exploring Physical Safety in Language Models
Sharon Levy, Emily Allaway, Melanie Subbiah, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 2407-2421
Open Access | Times Cited: 14
KoSBI: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Applications
Hwaran Lee, Seok‐Hee Hong, Joonsuk Park, et al.
(2023)
Open Access | Times Cited: 8
Target-Guided Dialogue Response Generation Using Commonsense and Data Augmentation
Prakhar Gupta, Harsh Jhamtani, Jeffrey P. Bigham
Findings of the Association for Computational Linguistics: NAACL 2022 (2022), pp. 1301-1317
Open Access | Times Cited: 12
Using In-Context Learning to Improve Dialogue Safety
Nicholas Meade, Spandana Gella, Devamanyu Hazarika, et al.
(2023)
Open Access | Times Cited: 7
AutoConv: Automatically Generating Information-seeking Conversations with Large Language Models
Siheng Li, Cheng Yang, Yichun Yin, et al.
(2023), pp. 1751-1762
Open Access | Times Cited: 6
Don’t Forget Your ABC’s: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems
Sarah E. Finch, James D. Finch, Jinho D. Choi
(2023), pp. 15044-15071
Open Access | Times Cited: 6
Goal Awareness for Conversational AI: Proactivity, Non-collaborativity, and Beyond
Yang Deng, Wenqiang Lei, Minlie Huang, et al.
(2023)
Open Access | Times Cited: 6
MoralDial: A Framework to Train and Evaluate Moral Dialogue Systems via Moral Discussions
Hao Sun, Zhexin Zhang, Fei Mi, et al.
(2023)
Open Access | Times Cited: 6
Bias Detection for Customer Interaction Data: A Survey on Datasets, Methods, and Tools
Andy Donald, Apostolos Galanopoulos, Edward Curry, et al.
IEEE Access (2023) Vol. 11, pp. 53703-53715
Open Access | Times Cited: 5
Click: Controllable Text Generation with Sequence Likelihood Contrastive Learning
Chujie Zheng, Pei Ke, Zheng Zhang, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2023), pp. 1022-1040
Open Access | Times Cited: 5
Improving Multi-label Malevolence Detection in Dialogues through Multi-faceted Label Correlation Enhancement
Yangjun Zhang, Pengjie Ren, Wentao Deng, et al.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022), pp. 3543-3555
Open Access | Times Cited: 7
SafeConv: Explaining and Correcting Conversational Unsafe Behavior
Mian Zhang, Lifeng Jin, Linfeng Song, et al.
(2023), pp. 22-35
Open Access | Times Cited: 4
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning
Ximing Lu, Faeze Brahman, Peter West, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 6863-6883
Open Access | Times Cited: 4
Page 1 - Next Page

Scroll to top